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Zou, Bo

Publications and source records attributed to Zou, Bo.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Competition between excitonic insulators and quantum Hall states in correlated electron–hole bilayers

Excitonic insulators represent a unique quantum phase of matter that enables the study of exotic quantum bosonic states. Strongly coupled electron–hole bilayers, which host stable dipolar exciton fluids with an exciton density that can be adjusted electrostatically, offer an ideal platform to investigate correlated excitonic insulators. On the basis of electron–hole bilayers made of MoSe2/hexagonal boron nitride/WSe2 heterostructures, here we study the behaviour of excitonic insulators in a perpendicular magnetic field. We report the observation of excitonic quantum oscillations in both Coulomb drag signals and electrical resistance at low to medium magnetic fields. Under a strong magnetic field, we identify multiple quantum phase transitions between the excitonic insulator phase and the bilayer quantum Hall insulator phase. These findings underscore the interplay between the electron–hole interactions and Landau-level quantization, and enable further exploration of quantum phenomena in composite bosonic insulators.

Qi, Ruishi↗
DOE OSTI2024

Electrical control of two-dimensional electron-hole fluids in the quantum Hall regime

We study the influence of quantizing perpendicular magnetic fields on the ground state of a bilayer with electron and hole fluids separated by an opaque tunnel barrier. In the absence of a field, the ground state at low carrier densities is a condensate of s-wave excitons that has spontaneous interlayer phase coherence. We find that a series of phase transitions emerge at strong perpendicular fields between condensed states and incompressible incoherent states with full electron and hole Landau levels. When the electron and hole densities are unequal, condensation can occur in higher angular momentum electron-hole pair states and, at weak fields, break rotational symmetry. Here, we explain how this physics is expressed in dual-gate phase diagrams, and predict transport and capacitively probed thermodynamic signatures that distinguish different states.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Critical magnetic fields and electron pairing in magic-angle twisted bilayer graphene

The velocities of the quasiparticles that form Cooper pairs in a superconductor are revealed by the upper critical magnetic field. Here we use this property to assess superconductivity in magic-angle twisted bilayer graphene (MATBG), which has been observed over a range of moiré band-filling, twist angle, and screening environment conditions. An average Fermi velocity can be defined as $v$$^{*}_{F}$ ≡ k B T c ℓ c /ℏ, where T c and ℓ c are the critical temperature and magnetic length, respectively. An advantage of this definition is that $v$$^{*}_{F}$ can be directly extracted from the existing experimental data. Mean-field theory calculations of upper critical fields in model superconductors are consistent with the expectation that Fermi velocities defined in this way are nearly independent of the strength of pairing interaction. Moreover, for fixed strength pairing interaction, minima in $v$$^{*}_{F}$ as a function of band filling are coincident with maxima in T c , as expected from the McMillan formula. Since no association between T c maxima and $v$$^{*}_{F}$ minima is present in MATBG experimental data, we argue that the pairing interaction in MATBG is strongly filling-factor dependent. Furthermore, any theory of MATBG superconductivity must explain this dependence, which is apparently primarily responsible for the observed superconducting domes.

2-dimensional systems↗
DOE OSTI2022

Pressure-stimulus-responsive behaviors of core–shell InP/ZnSe nanocrystals: remarkable piezochromic luminescence and structural assembly

Piezochromic luminescence materials with optical properties can be adjusted (the colors most sensitive to the human eye range from red to green) to provide powerful means for information acquisition in various applications. Inorganic quantum dots, typically based on heavy metals such as cadmium and lead, have congenital advantages as luminescence materials, including strong inoxidizability and excellent photoelectric properties. However, small band-gap shifts under pressure have hindered the development of inorganic-based piezochromic materials. In this study, we combined in situ high-pressure photoluminescence (PL) and absorption measurements with synchrotron X-ray scattering spectra to elucidate the remarkable modulation of optical properties and morphologies by pressure, particularly that of the piezochromic luminescence, in all-inorganic core–shell InP/ZnSe nanocrystals (NCs). We observed a stepwise PL color change from red to green, and an ultrabroad bandgap tunability of 0.46 eV was observed from 1.99 to 2.45 eV in the pressure range of 14.2 GPa for InP/ZnSe NCs. Moreover, two-dimensional (2D) InP/ZnSe nanosheets were synthesized by the stress-driven attachment of nanoparticles. These results demonstrate the ability of the pressure-stimulus response to trigger remarkable piezochromic luminescence and 2D nanosheet assembly in InP/ZnSe NCs, which paves the way for new applications of all-inorganic InP-based semiconductor NCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Modeling household online shopping demand in the U.S.: a machine learning approach and comparative investigation between 2009 and 2017

Despite the rapid growth of online shopping and research interest in the relationship between online and in-store shopping, national-level modeling and investigation of the demand for online shopping with a prediction focus remain limited in the literature. Here, this paper differs from prior work and leverages two recent releases of the U.S. National Household Travel Survey (NHTS) data for 2009 and 2017 to develop machine learning (ML) models, specifically gradient boosting machine (GBM), for predicting household-level online shopping purchases. The NHTS data allow for not only conducting nationwide investigation but also at the level of households, which is more appropriate than at the individual level given the connected consumption and shopping needs of members in a household. We follow a systematic procedure for model development including employing Recursive Feature Elimination algorithm to select input variables (features) in order to reduce the risk of model overfitting and increase model explainability. Among several ML models, GBM is found to yield the best prediction accuracy. Extensive post-modeling investigation is conducted in a comparative manner between 2009 and 2017, including quantifying the importance of each input variable in predicting online shopping demand, and characterizing value-dependent relationships between demand and the input variables. In doing so, two latest advances in machine learning techniques, namely Shapley value-based feature importance and Accumulated Local Effects plots, are adopted to overcome inherent drawbacks of the popular techniques in current ML modeling. The modeling and investigation are performed at the national level, with a number of findings obtained. The models developed and insights gained can be used for online shopping-related freight demand generation and may also be considered for evaluating the potential impact of relevant policies on online shopping demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Pressure-induced excimer formation and fluorescence enhancement of an anthracene derivative

Excimer materials have been widely studied and have generated significant interest for their applications in many optoelectronic devices. However, a thorough investigation of the entire process involved in excimer formation, enhancement, and annihilation in solid materials is still lacking. Here we designed a crystal based on an anthracene derivative with dissociative, molecular-ordered dimer assembly, and studied the formation and evolution of an anthracene excimer as a function of pressure. During the initial stage of pressurization, the fluorescence intensity arising from anthracene monomers gradually decreases. Therefore, with continued compression, the two anthracene units become increasingly closer allowing strong intermolecular π–π interactions to develop that lead to excimer formation at 3.5 GPa, accompanied with a phase transition. The fluorescence intensity then keeps increasing with pressure and reaches its maximum at 5.6 GPa due to the strengthening of the excimer and the increased structural defects. Meanwhile the fluorescence color shows a continuous redshift, which initially results from conformation planarization and then excimer evolution. After releasing pressure back to ambient conditions, the structural changes in the sample are reversible, while the fluorescence signal preserves some high-pressure features due to the partial retention of the π–π interactions between the anthracene dimers. This study reveals the evolution of an excimer and its intrinsic photophysical properties, and provides guidance for future research on pressure-sensitive fluorescent devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Resilient co-expansion planning between gas and electric distribution networks against natural disasters

Resiliently designed and constructed integrated gas-electric distribution networks (GEDNs) against natural disasters are crucial to social welfare. In this study, a two-stage robust optimisation-based co-expansion planning model is proposed to attain an integrated GEDN with a given resilience level, by optimising the investment strategies of hardening and selective expansion of power distribution feeders and natural gas pipelines, as well as the location and capacity of natural-gas-fired distributed generation. In the first stage, the overall annual investment and operation cost is minimised under normal operation conditions while in the second stage, the feasibility of the investment decisions under the identified worst-case natural disaster scenario is checked with an adjustable load shedding cost criterion. The proposed model is formulated as a mixed integer second-order cone programming problem with the column and constraint generation algorithm employed to seek the optimal solution. Case studies on two integrated GEDNs demonstrate the performance of the proposed methodology.

Zou, Bo↗
DOE OSTI2020

Pressure Effects on the Electronic and Optical Properties in Low-Dimensional Metal Halide Perovskites

Metal halide perovskites have shown enormous potential in perovskite solar cells and light-emitting diodes and made unprecedented progress in the past decade. Additionally, pressure engineering as an effective technique can systematically modify the electronic structures and physical properties of functional materials. Low-dimensional metal halide perovskites (0D, 1D, and 2D) with a variety of compositions have soft lattices that allow pressure to drastically modulate their structures and properties. High-pressure investigations have obtained a comprehensive understanding of their structure–property relationships. Simultaneously, discoveries of novel pressure-driven properties, such as metallization and partially retained band gap narrowing have contributed significantly to the further development of such materials. In this work, we mainly highlight the effect of pressure on the properties and structures of low-dimensional metal halide perovskites, which is essential for designing new perovskite materials and advancing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pressure-Induced Multidimensional Assembly and Sintering of CuInS 2 Nanoparticles into Lamellar Nanosheets with Band Gap Narrowing

Two-dimensional (2D) nanomaterials have fascinating structural, electrical, and optical properties, especially strong excitonic effects due to decreased dielectric screening. However, constructing 2D ultrathin nanomaterials, with the exception of layered materials, remains a challenge. In this work, we successfully realize oriented attachment on guiding one-dimensional chalcopyrite CuInS 2 nanocrystal (NC) formation and 2D assembly into lamellar nanosheets by applying pressure-driven sintering of zero-dimensional CuInS2 nanoparticles (NPs). We discuss the atomic-level mechanism of such phenomena and illustrate a pressure-driven processing diagram that reveals the sintering process of NPs coordinated by pressure and structural transformation. Optical measurements exhibit that the band gap has a narrowing by 0.21 eV compared with the initial 2.03 eV upon decompression to ambient conditions. Our findings represent a significant step forward in gaining an in-depth understanding of the pressure-driven morphology engineering of nanomaterials and provide a promising strategy to prepare 2D NCs, thereby greatly increasing the choice of materials for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning for international freight transportation management: A comprehensive review

Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.

Data sources↗
DOE OSTI2020

Selected Negative Linear Compressibilities in the Metal–Organic Framework of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6

Negative linear compressibility (NLC) is a rare high-pressure observation that lattice contraction is accompanied by the structural expansion along a specific direction. Generally, this counterintuitive phenomenon only derives from the intrinsic structural characteristics of materials and cannot be tuned by external perturbations. Searching for an effective method to control NLC effect is still a challenge in both chemical and material science. In this work, we successfully discover and select the NLC behaviors in the metal-organic framework (MOF) of [Cu(4,4'-bpy) 2 (H 2 O) 2 ]·SiF 6 (Cu(bpy)·SiF) through controlling the pressure conditions therein. The NLC effect of Cu(bpy)·SiF originates from the wine-rack mechanism that quasi-square grids transfer to rhombic ones with the structural expansion along the diagonal direction at high pressure. Meanwhile, both of the pressure range and magnitude of the NLC responses are enlarged with optimized pressure conditions. This study not only presents the intriguing selected NLC behaviors of a MOF but also proves the effects of pressure conditions on NLC, which offers promising strategies for further design and applications of NLC materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗